2013 Industrial Math/Stat Modeling Workshop for Graduate Students 발표자 : 장기훈

2013 Industrial Math/Stat Modeling Workshop for Graduate Students

발표자 : 장기훈

자기소개서 준비 합격통보 비자 발급 비행기 예약 회화연습 출국

PREPERATION

한국 노스캐롤라이나

11시간+6시간 !!!!

SAMSI

Statistical and Applied Mathematical Sciences Institute

NSF, Duke, NCSU, UNC, NISS SAMSI's  mission is to forge a synthesis of

the statistical and the applied mathematical sciences to confront the very hardest and most important data, model-driven scientific challenges

SAMSI

2013 Industrial Math/Stat Modeling Workshop for Graduate Students

July 15-23, 2013 Objective was to expose graduate students

in mathematics, engineering, and statistics to challenging and exciting real-world problems arising in industrial and government laboratory research

8-9 am : Breakfast 9 am ~ 5 am : Working sessions

Make the report Presentation of results

SCHEDULE

PROJECTS

Numerical Modeling and Simulation of Fluid Flow with Application to Current Environmental Challenges

Burden of Sexual Transmitted Diseases in the US: Trend Analysis of Incidence Rates

Photoresponsive Polymer Beam Design for Solar Concentrator Self-steering Heliostats

Microbes and Molecules: A Microscopic Analysis of Asthma

Network Analytics and Visualization in Healthcare Urban Route Planning from Aerial Imagery

Burden of Chlamydia in the US: Trend Analysis of Incidence Rates

Ridouan Bani, Anna D. Broido, Andrew F. Brouwer,

Shih-Han Chang, Kihoon Jang, Qianqian Ma, Jiani Yin

Faculty Mentors: Howard Chang, Emory Problem Presenter: Simone Gray, CDC

Chlamydia and reporting delays Graphical trends Modeling National and State level incidence

rates Modeling incidence rates by population

demographics Hierarchical modeling

Outline

Most commonly reported bacterial STI in the US.

Caused by bacterium Chlamydia trachomatis.

Though it is often asymptomatic, especially in men, Chlamydia can lead to other serious illnesses in both men and women.

Reporting delays (administrative) mean current incidence data is unavailable.

Chlamydia

National Incidence Rates: By Race

African Americans had about 9 times higher incidence than Whites and Asians

Use available data 2000-2011 to project chlamydia incidence rates with quantified uncertainty for 2012-2013 for: The United States Each state Each demographic group

Sex Race (American Indian, Asian, Black, Hispanic, White)

Create a hierarchical model to incorporate spatial effects on variations in incidence rates

Objectives

Assume incident cases follow a Poisson distribution Natural for positive counts Log-transformed rates are not normally

distributed Y= incident cases, λ = rate, N = population,

xi = year, spatial, and demographic variables

Poisson Regression

Average absolute relative deviation (AARD)

Model Assessment

Akaike information criterion (AIC)

National and State Model

AARD calculated over 2000-2011 incident cases

Model

Variables AIC AARD-National

AARD-State

1 Year 634406

1.2% 30.5%

2 Year + State

98631 1.2% 7.3%

Model 1: National level projectionsPopulation projected linearly

Demographic Model

Model Variables AIC AARD

3 Year + Sex + Race 118525 13.1%

4 Year + Sex × Race 53191 7.4%

5 Year × Race + Sex 102259 12.3%

6 Year × Race + Sex × Race 36831 6.6%

7 Year × Sex × Race 8987 3.3%

AARD calculated over 2000-2011 incident cases

Note the importance of the Sex-Race interaction over the Year-Race interaction.

Incidence follows strong temporal trends that vary spatially and demographically.

Poisson regression allows reasonable projection for recent and current incidence.

Increased complexity does not necessarily improve predictions for aggregate data.

Current approach for uncertainty quantification gives conservative estimates.

Conclusions

Improve confidence in projections by training data on 2000-2009 data and testing on 2010-2011 for all models

Include specific race-state interactions (particularly for American Indian populations in certain states)

Include spatial correlation terms that decrease with distance.

Investigate ways to relax the Poisson assumption and account for over-dispersion

Project incidence beyond 2013

Future Work

PROGRAM

WORKING

Compile the data Analysis the data by using R Make simple statistic data Double check the data

소감

Good thing 여러 나라 학생과 학문적 교류 더 넓은 시각으로 수학을 공부 Bad thing 짧은 기간

THANK YOU